A data correction-based steam turbine extraction dehumidification calculation method

Abstract

The application discloses a steam turbine extraction dehumidification calculation method based on data correction, comprising the following steps: 1) constructing a low-pressure cylinder-heat recovery heater system heat balance model; 2) establishing a dehumidification model equation for a steam turbine and associated extraction pipeline in which a dehumidification technology is adopted; 3) according to the model involved in step 2), generating a mean value and a covariance matrix by using measured data and instrument uncertainty information of a power plant in a certain period and information of measuring point; 4) according to the measured data of step 3), solving the heat balance model and the dehumidification model to obtain system unknown variable data; 5) according to the unknown variable calculation result, calculating a Jacobian matrix of a current system residual with respect to known parameter variables through a redundant balance equation; 6) according to the obtained Jacobian matrix, calculating a known parameter correction amount; and 7) according to the calculated parameter correction amount, calculating corrected measuring point values and extraction dehumidification parameters. The application can realize calculation of unknown parameters in a steam turbine.

Description

Technical Field

[0001] This invention belongs to the field of steam turbine parameter calculation methods, specifically relating to a steam turbine extraction dehumidification calculation method based on data correction. Background Technology

[0002] As a key component of the power plant's thermal system, the steam turbine is equipped with various types of measuring instruments at its inlet and outlet to help power plant operators monitor its operation in real time. However, due to unpredictable factors in actual measurements, these instruments inevitably produce errors compared to standard values, leading to incorrect judgments by operators regarding the current operating status. Furthermore, due to current technological limitations and engineering applications, these measuring instruments can only measure the turbine's inlet and outlet temperatures, pressures, and flow rates, making it difficult to directly measure the dryness of the wet steam. Yet, the dryness of the steam turbine's final stage is a crucial parameter for researchers, directly impacting its safe and stable operation. Currently, steam turbines often employ various dehumidification technologies, introducing the separated saturated water into a regenerator to improve the dryness of the steam at the turbine's final stage and increase energy efficiency. However, since the steam turbine in an actual power plant is a single unit, it's impossible to place measuring instruments there. Therefore, it's difficult to determine the dryness of the steam after dehumidification based solely on inlet and outlet parameters, making it challenging to understand the turbine's final stage operating status. The presence of measuring instrument errors further complicates accurate and reliable calculations.

[0003] To achieve accurate and reliable calculations of extraction steam parameters and terminal internal parameters after dehumidification of power plant steam turbines, it is necessary to propose a calculation method that meets the requirements of real-world complex situations and can calculate unknown parameters of steam turbine extraction dehumidification based on component characteristics and operating conditions. In this field, there are classic calculation methods that use turbine separation efficiency to calculate the dehumidification effect of steam turbines. However, this method measures dehumidification efficiency by mass, making it difficult to simultaneously meet the calculation requirements of energy balance during extraction and turbine terminal parameters. Furthermore, in real-world power plant calculations, it faces difficulties in solving the problem and increased complexity, thus limiting the application of this method. Summary of the Invention

[0004] The purpose of this invention is to provide a data-corrected calculation method for steam turbine extraction dehumidification, enabling the calculation of unknown parameters within the steam turbine. This invention utilizes the change in the enthalpy of the working fluid to measure dehumidification efficiency and combines it with a data correction method to correct turbine parameters, significantly improving the accuracy of unknown parameter calculations. The proposed method fully utilizes the measurement redundancy of the regenerator section, improving the stability and accuracy of the calculations, and can be widely applied in the calculation of steam turbine-regenerator systems.

[0005] The present invention is achieved using the following technical solution:

[0006] A calculation method for steam turbine extraction dehumidification based on data correction includes the following steps:

[0007] 1) Construct a thermal balance model for the low-pressure cylinder-regenerative heater system;

[0008] 2) For the heat balance model constructed in step 1), establish the dehumidification model equations for the steam turbine and its associated extraction steam pipeline that employ dehumidification technology;

[0009] 3) Based on the measurement point information involved in the model established in step 2), use the measurement data and instrument uncertainty information of the power plant within a certain period of time to generate the mean and covariance matrix;

[0010] 4) Based on the measurement data from step 3), solve the heat balance model and dehumidification model to obtain the data of unknown variables in the system;

[0011] 5) Based on the calculation results of the unknown variables in step 4), calculate the Jacobian matrix of the current system residuals with respect to the known parameter variables using the redundancy balance equation;

[0012] 6) Calculate the correction amount of the known parameters based on the Jacobian matrix obtained in step 5);

[0013] 7) Based on the parameter correction amount calculated in step 6), calculate the corrected measurement point value and the steam extraction dehumidification parameter.

[0014] A further improvement of this invention is that, in step 1), the following relationship is established using measurement information from the power plant:

[0015] y = s(x), z = g(x, y) (1)

[0016] In the formula, x represents the known parameters of the low-pressure cylinder or regenerative heater of the power plant, including the vector of measured values ​​from relevant measuring points in the actual layout and the known component characteristic parameters; the measuring points include three types: flow rate, temperature, and pressure; the component characteristic parameters include the heat transfer coefficient and heat transfer area of ​​the heat exchanger and the isentropic efficiency of the turbine; y represents the unknown physical property parameters obtained from the measured values ​​using the working fluid property relationship; z represents the unknown parameters in the power plant system, which are certain physical quantities calculated using known measured values ​​and unknown physical property parameters, or the transfer and transformation of measured values, such as the increase or decrease in mass flow rate when the working fluid merges or splits in the pipeline; the system heat balance model is established based on the two principles of mass balance and energy balance, and for a certain part with the index i, the following mass balance equation exists:

[0017] f m,i =m in,i -m out,i =0(2)

[0018] In the formula, f m,i m represents the residual of the mass balance equation for component i.in,i m represents the total flow rate of the working fluid input to component i. out,i Let represent the total flow rate of the working fluid exiting component i, with all flow rates calculated using absolute values; for a given component, the following energy balance equation applies:

[0019] f e,i =e in,i -e out,i =0(3)

[0020] In the formula, f e,i e represents the residual of the energy balance equation for component i. in,i e represents the total input energy of a component i. out,i Let represent the total energy flowing out of component i; all energy values ​​are calculated using absolute values; by combining the balance equations of each component, the residual vector of the overall system balance equation is obtained as follows:

[0021] R=zx′(4)

[0022] In the formula, R represents the residual vector of the current equilibrium equation of the system; x′ represents some known parameters in the system, specifically the remaining known parameters in the system other than those used for solving the basic conditions for unknown parameters.

[0023] A further improvement of the present invention is that, in step 2), the dehumidification efficiency η... moist The definition is as follows:

[0024]

[0025] In the formula, h i,1 Indicates the enthalpy of the working fluid at the inlet of the dehumidifier; h i,2 Indicates the enthalpy of the working fluid at the outlet of the dehumidifier; h i,sat This represents the saturated water enthalpy value corresponding to the current pressure of the working fluid in the dehumidifier; x i,1 Indicates the dryness of the working fluid at the inlet of the dehumidifier;

[0026] The following relationship applies to the mass and energy balance of dehumidifiers:

[0027] m i,1 =m i,2 +m o,1 (6)

[0028] m i,1 h i,1 =m i,2 h i,2 +m o,1 h o,1 (7)

[0029] In the formula, m i,1 This indicates the flow rate of the working fluid at the inlet of the dehumidifier; m i,2This indicates the working fluid flow rate at the outlet of the dehumidifier; m o,1 Indicates the working fluid flow rate at the dehumidification steam extraction pipeline; h o,1 This indicates the enthalpy value of the working fluid at the dehumidification extraction steam pipeline.

[0030] The heat exchange power of the shell side of the regenerator after dehumidification and steam extraction is:

[0031] Q h =m d,1 (h d,1 -h d,2 )+m s (h s -h d,2 )+m o,1 (h o,1 -h d,2 (8)

[0032] In the formula, Q h Indicates the heat exchange power of the regenerator; m d,1 Indicates the upper-level drainage flow rate; h d,1 Indicates the hydrophobic enthalpy of the upper level; h d,2 Indicates the hydrophobic enthalpy value of this stage; m s Indicates the flow rate of other heating steam; h s Indicates other heating vapor enthalpy values;

[0033] By varying the parameters of the feedwater on the tube side of the regenerator heater, and based on energy balance, the following equilibrium relationship is obtained:

[0034] Q h -m h,i (h h,o -h h,i )=0 (9)

[0035] In the formula, m h,i Indicates the feedwater flow rate on the tube side of the regenerator heater; h h,o Indicates the enthalpy value of the feedwater outlet on the tube side of the regenerator heater; h h,i This represents the enthalpy value of the feedwater inlet on the tube side of the regenerator; thus, the calculation relationship from the inlet and outlet parameters of the separation and dehumidification device, and the parameters of the extraction steam pipeline to the corresponding measured values ​​of the regenerator measuring points is established.

[0036] A further improvement of the present invention is that, in step 3), the operating parameter M of a certain component of the system over a period of time is... i A series of measurement values ​​were obtained by selecting n measurement results: M i,1 M i,2 ,…,M i,n Then the mean value of the measured values ​​at this measuring point is:

[0037]

[0038] In the formula, This is the estimated mean value at this measuring point; in addition to the mean of the measured values, the instrument uncertainty also needs to be used to measure the randomness of the fluctuations in the measured values ​​at the measuring point over a period of time, thus obtaining the covariance matrix X between the measured values ​​at the measuring point. c Its elements are calculated as follows:

[0039]

[0040] In the formula, x ij These are the elements in the covariance matrix; The variance of the measured values ​​at the measuring point; r ij The correlation coefficient between the measuring points is determined based on historical operating data of the actual power plant and combined with engineering experience.

[0041] A further improvement of this invention is that, in step 4), for the dehumidification device and the corresponding regenerative heater in the steam turbine, the following set of equations is obtained based on the mass, energy balance, and dehumidification model:

[0042]

[0043] This system of equations is a multivariate nonlinear system, which is solved using the Newton-Raphson iterative method. Let F(x) = 0 for this nonlinear system of equations. Then, the Jacobian matrix of this system of equations is defined as:

[0044]

[0045] After obtaining its Jacobian matrix, the following iterative scheme is constructed:

[0046] x (k+1) =x (k) -J -1 (x (k) )F(x (k) (14)

[0047] In the formula, k is the number of iterations, x (k) Let x represent the solution to the k-th iteration of the system of equations; J -1 (x (k) ) represents x (k) The inverse of the Jacobian matrix; starting from k=0, and setting the iteration precision ε, the iteration process should solve the following system of linear equations:

[0048] J(x (k) )d=-F(x (k) (15)

[0049] Solving for d from the above equation, if |d| < ε, it indicates that the iteration has converged, meeting the accuracy requirement, and the iteration process terminates; otherwise, set x. (k+1) =x (k) +d(k) Continue iteratively to solve the problem.

[0050] A further improvement of this invention is that, in step 5), in order to measure the overall error level of the system under its current operating conditions, the redundant part of the balance equation is used to calculate the system residual, thereby obtaining the Jacobian matrix J of the redundant balance equation with respect to the known parameter x. R,x To calculate the Jacobian matrix, it is necessary to separately calculate the Jacobian matrix J of the unknown parameter z of the power station with respect to the known parameter x. z,x And the Jacobian matrix J of the redundant balance equation with respect to the unknown parameter z of the power plant R,z The Jacobian matrix J is calculated using the chain rule. R,x for:

[0051] J R,x =J R,z J z,x (16).

[0052] A further improvement of the present invention is that, in step 6), the calculated Jacobian matrix J is used... R,x The residuals of the system's redundant balance equations are calculated using the known parameter variables' means and elements of the covariance matrix. Based on the above conditions, the correction amounts for all known parameters within the system can be calculated. The mean values ​​of the unknown parameters and the system's balance equation residuals are then calculated based on the mean values ​​of the known system parameters.

[0053]

[0054]

[0055] In the formula, and These are the mean vectors of the unknown physical property parameters, known parameters, and unknown parameters in the system, respectively. and Let X be the mean vector of the residuals and some known parameters in the system, respectively; from this, the covariance matrix X of the residual vector of the system equilibrium equation can be calculated. R :

[0056]

[0057] Given the parameter correction amount c, we have the following constrained optimization problem:

[0058]

[0059] The objective of this constrained optimization problem is to minimize the optimization function ξ(c), i.e., minimize the correction amount, while ensuring that the residuals of the system equilibrium equations are zero. Applying the Lagrange multiplier method to the above optimization problem and introducing the Lagrange multiplier variable λ, the problem is equivalently transformed into the following form:

[0060]

[0061] The expression for the correction quantity obtained by solving based on the stationary point conditions is as follows:

[0062]

[0063] Since λ is still unknown in the above equation, both sides of the equation are multiplied on the left by the Jacobian matrix J. R,x The above expression can be transformed into the following form:

[0064] J R,x c = X c λ (23) Based on the constraints of this optimization problem The Lagrange multipliers are:

[0065]

[0066] Substituting the above equation back into equation (23), we obtain the final solution for the correction:

[0067]

[0068] Through the above process, the correction amount of each known parameter is solved; under the condition of minimizing the optimization objective function, the residual of the system redundancy balance equation is reduced to the minimum.

[0069] A further improvement of the present invention is that, in step 7), the final solution c of the calculated correction amount is appended as the final correction vector to the mean vector of the original known parameters. The above steps complete the correction of the known parameters. The mean vector of the corrected known parameters is as follows:

[0070]

[0071] Compared with the prior art, the present invention has at least the following beneficial technical effects:

[0072] Existing classical calculation methods use mass relations to measure dehumidification efficiency, thus representing the mass of saturated water separated. However, this method requires repeated calculations of pipeline parameters when applied to actual steam extraction pipelines. Because it uses mass relations to measure dehumidification efficiency, it cannot directly correct the efficiency from an energy perspective using the power of the turbine and heat exchanger. This can easily lead to calculation results that deviate significantly from the normal range under various operating conditions of real units. The calculation method proposed in this invention, however, measures dehumidification efficiency from an energy perspective by using changes in the enthalpy of the working fluid. It can use the power of the turbine and heat exchanger to correct the current dehumidification efficiency when parameters change under different operating conditions, and can further calibrate the parameters of related pipelines and components.

[0073] Since this method measures the dehumidification efficiency of the steam turbine from an energy perspective, it can directly calculate the inlet enthalpy of the downstream stage of the steam turbine, effectively ensuring the accuracy of the steam turbine solution. Furthermore, it can establish an energy-mass balance relationship with the corresponding regenerator based on the mass balance relationship, making full use of the measurement redundancy of the regenerator section to achieve data correction for the steam turbine-regenerator system, thus maximizing the accuracy of the system calculation. Attached Figure Description

[0074] Figure 1 This is a flowchart illustrating the process of correcting turbine extraction dehumidification parameters based on data correction.

[0075] Figure 2 This is a diagram showing the measuring points and connection relationships of a low-pressure cylinder-regenerative heater system in a power plant. Detailed Implementation

[0076] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0077] Please see Figure 1 As shown, this invention provides a calculation method for turbine extraction dehumidification based on data correction, comprising the following steps:

[0078] 1) Construct a heat balance model for the low-pressure cylinder-regenerative heater system, specifically by establishing the following relationship using measurement information from the power plant:

[0079] y = s(x), z = g(x, y) (1)

[0080] In the formula, x represents the known parameters of the low-pressure cylinder or regenerative heater of the power plant, including the vector of measured values ​​from relevant measuring points in the actual layout and the known component characteristic parameters. Measuring points typically include three types: flow rate, temperature, and pressure, while component characteristic parameters include the heat transfer coefficient and heat transfer area of ​​the heat exchanger, the isentropic efficiency of the turbine, etc. y represents the unknown physical property parameters obtained through the measured values ​​and the working fluid property relationships, such as the enthalpy and entropy values ​​of the working fluid in a certain section of the pipeline in the system. z represents the unknown parameters in the power plant system, which are certain physical quantities (such as power and heat transfer power) calculated using known measured values ​​and unknown physical property parameters, or the transfer and transformation of measured values, such as the increase or decrease in mass flow rate when the working fluid merges or splits in the pipeline. The system thermal balance model is established based on the two principles of mass balance and energy balance. For a certain component (number i), the following mass balance equation exists:

[0081] f m,i =m in,i -m out,i =0(2)

[0082] In the formula, f m,i m represents the residual of the mass balance equation for component i. in,i m represents the total flow rate of the working fluid input to component i. out,i This represents the total flow rate of the working fluid exiting component i. All flow rates are calculated using absolute values, and positive or negative signs are not required to indicate direction. For a given component, the following energy balance equation applies:

[0083] f e,i =e in,i -e out,i =0(3)

[0084] In the formula, f e,i e represents the residual of the energy balance equation for component i. in,i e represents the total input energy of a component i. out,i This represents the total energy flowing out of component i. For a given component, the total energy includes not only the energy carried by the working fluid but also the input and output work. All energy values ​​are calculated using absolute values; positive and negative signs are not required to indicate direction. Combining the equilibrium equations of each component, the residual vector of the overall system equilibrium equations is obtained as follows:

[0085] R=zx′(4)

[0086] In the formula, R represents the residual vector of the current equilibrium equation of the system; x′ represents some known parameters in the system, specifically the remaining known parameters in the system other than those used for solving the basic conditions for unknown parameters.

[0087] 2) For steam turbines employing dehumidification technology and their associated extraction steam pipelines, a dehumidification model equation is established. In this method, the dehumidification efficiency η... moist The definition is as follows:

[0088]

[0089] In the formula, h i,1 Indicates the enthalpy of the working fluid at the inlet of the dehumidifier; h i,2 Indicates the enthalpy of the working fluid at the outlet of the dehumidifier; h i,sat This represents the saturated water enthalpy value corresponding to the current pressure of the working fluid in the dehumidifier; x i,1 This indicates the dryness of the working fluid at the inlet of the dehumidifier. The above definition of dehumidification efficiency establishes the relationship between the change in the enthalpy of the working fluid before and after dehumidification, measuring the dehumidification effect of the component from an energy perspective. This dehumidification efficiency calculation formula does not involve the mass relationship of the working fluid before and after dehumidification. The following relationship applies to the mass and energy balance of the dehumidifier:

[0090] m i,1 =m i,2 +m o,1 (6)

[0091] m i,1 h i,1 =m i,2 h i,2 +m o,1 h o,1 (7)

[0092] In the formula, m i,1 This indicates the flow rate of the working fluid at the inlet of the dehumidifier; m i,2 This indicates the working fluid flow rate at the outlet of the dehumidifier; m o,1 Indicates the working fluid flow rate at the dehumidification steam extraction pipeline; h o,1 This represents the enthalpy of the working medium at the dehumidification extraction steam pipeline. Since the outlet working medium flow rate and enthalpy after dehumidification, as well as the working medium flow rate and enthalpy in the dehumidification extraction steam pipeline, are all unknown variables in a real power plant system, it is necessary to establish a calculation relationship with the corresponding regenerative heater. For the sake of overall unit thermal economy, the regenerative heater in a real power plant typically includes, on the shell side, upper-stage condensate and other heating steam, in addition to the extraction steam. Therefore, the shell-side heat exchange power of the regenerative heater after the aforementioned dehumidification extraction is:

[0093] Q h =m d,1 (h d,1 -h d,2 )+m s (h s -h d,2 )+m o,1 (h o,1 -h d,2 (8)

[0094] In the formula, Q h Indicates the heat exchange power of the regenerator; m d,1 Indicates the upper-level drainage flow rate; hd,1 Indicates the hydrophobic enthalpy of the upper level; h d,2 Indicates the hydrophobic enthalpy value of this stage; m s Indicates the flow rate of other heating steam; h s This indicates other heating vapor enthalpy values.

[0095] By varying the parameters of the feedwater on the tube side of the regenerator heater, and based on energy balance, the following equilibrium relationship can be obtained:

[0096] Q h -m h,i (h h,o -h h,i )=0 (9)

[0097] In the formula m h,i Indicates the feedwater flow rate on the tube side of the regenerator heater; h h,o Indicates the enthalpy value of the feedwater outlet on the tube side of the regenerator heater; h h,i This represents the enthalpy value at the feedwater inlet on the tube side of the regenerator heater. This establishes a calculation relationship between the inlet and outlet parameters of the separation and dehumidification device, the parameters of the extraction steam pipeline, and the corresponding measured values ​​at the regenerator heater measuring points.

[0098] 3) Generate the mean and covariance matrix based on the measurement data and instrument uncertainty information of the power plant during a certain period.

[0099] The above section completed the establishment of the system parameter balance relationship model for the power plant involved in this case. The input parameters of the model are the measured values ​​of the measuring points arranged in the actual power plant. The power plant's daily operation is generally stable, but there are some state fluctuations and the random influence of short-term instrument measurements. Therefore, the measured values ​​input to the model should not be the instantaneous values ​​of the power plant's operation, but rather the average of the measured values ​​over a period of time to measure the current operating status of the system. For the operating parameter M of a certain component of the system over a period of time... i A series of measurement values ​​were obtained by selecting n measurement results: M i,1 M i,2 ,…,M i,n Then the mean value of the measured values ​​at this measuring point is:

[0100]

[0101] In the formula, This is an estimate of the mean at this measuring point. In addition to the mean of the measured values, instrument uncertainty is also needed to measure the randomness of the fluctuations in the measured values ​​at the measuring point over a period of time, which yields the covariance matrix X between the measured values ​​at the measuring point. c Its elements are calculated as follows:

[0102]

[0103] In the formula, xij These are the elements in the covariance matrix; The variance of the measured values ​​at the measuring point; r ij The correlation coefficient between the measuring points is determined based on historical operating data of the actual power plant and engineering experience. The covariance matrix described above reflects the statistical characteristics of the current system operation, characterizing the statistical distribution of the measured values ​​and serving as the primary basis for subsequent corrections to the measured values.

[0104] 4) Solve the heat balance model and dehumidification model to obtain data on unknown variables of the system.

[0105] For the dehumidification unit and corresponding regenerative heater in the steam turbine, based on the aforementioned mass, energy balance, and dehumidification model, the following set of equations can be obtained:

[0106]

[0107] This system of equations is a multivariate nonlinear system of equations, which can be solved using the Newton-Raphson iterative method. Let F(x) = 0 be the equation of this nonlinear system. Then, the Jacobian matrix of this system of equations is defined as:

[0108]

[0109] After obtaining its Jacobian matrix, the following iterative scheme is constructed:

[0110] x (k+1) =x (k) -J -1 (x (k) )F(x (k) (14)

[0111] In the formula, k is the number of iterations, x (k) Let x represent the solution to the k-th iteration of the system of equations; J -1 (x (k) ) represents x (k) The inverse of the Jacobian matrix; starting from k=0, and setting the iteration precision ε, the iteration process should solve the following system of linear equations:

[0112] J(x (k) )d=-F(x (k) (15)

[0113] Solving for d from the above equation, if |d| < ε, it indicates that the iteration has converged, meeting the accuracy requirement, and the iteration process terminates; otherwise, set x. (k+1) =x (k) +d (k) Continue iteratively to solve the problem.

[0114] 5) Calculate the Jacobian matrix of the current system residuals with respect to the known parameter variables using the redundancy balance equation.

[0115] To measure the overall error level of the system under its current operating conditions, the system residuals can be calculated using the redundant part of the above balance equations. From this, the Jacobian matrix J of the redundant balance equations with respect to the known parameter x can be obtained. R,x To calculate the Jacobian matrix mentioned above, it is necessary to calculate the Jacobian matrix J of the unknown parameter z of the power plant with respect to the known parameter x. z,x And the Jacobian matrix J of the redundant balance equation with respect to the unknown parameter z of the power plant R,z The Jacobian matrix J can be calculated using the chain rule. R,x for:

[0116] J R,x =J R,z J z,x (16)

[0117] 6) Calculate the correction amount for the known parameters.

[0118] Based on the Jacobian matrix J calculated above R,x The residuals of the system's redundant balance equations are calculated using the known parameter variables' means and elements of the covariance matrix. Based on the above conditions, the correction amounts for all known parameters within the system can be calculated. The mean values ​​of the unknown parameters and the mean values ​​of the system's balance equation residuals can be calculated based on the mean values ​​of the known system parameters.

[0119]

[0120]

[0121] In the formula, and These are the mean vectors of the unknown physical property parameters, known parameters, and unknown parameters in the system, respectively. and These are the mean vectors of the residuals and some known parameters in the system, respectively. From this, the covariance matrix X of the residual vector of the system equilibrium equation can be calculated. R :

[0122]

[0123] Given the parameter correction amount c, we have the following constrained optimization problem:

[0124]

[0125] The objective of this constrained optimization problem is to minimize the optimization function ξ(c), i.e., minimize the correction amount, while ensuring the residuals of the system equilibrium equations are zero. Applying the Lagrange multiplier method to the above optimization problem and introducing the Lagrange multiplier variable λ, the problem can be equivalently transformed into the following form:

[0126]

[0127] It should be noted that the additional term with a constant coefficient of -2 introduced in the Lagrange multiplier method at this point is for convenience in subsequent solutions and has no impact on the calculation results. The expression for the correction quantity obtained from the stationary point condition is as follows:

[0128]

[0129] Since λ is still unknown in the above equation, both sides of the equation are multiplied on the left by the Jacobian matrix J. R,x The above formula can be transformed into the following form:

[0130] J R,x c = X c λ (23)

[0131] Based on the constraints of this optimization problem The Lagrange multipliers can be solved as follows:

[0132]

[0133] Substituting the above equation back into equation (23), we obtain the final solution for the correction:

[0134]

[0135] Through the above process, the correction amount of each known parameter can be solved; under the condition of minimizing the optimization objective function, the residual of the system redundancy balance equation is reduced to the minimum.

[0136] 7) Calculate the corrected measurement point values ​​and steam extraction dehumidification parameters.

[0137] The final solution c, obtained through the above calculations, can be used as the final correction vector and appended to the mean vector of the original known parameters. The above steps complete the correction of the known parameters. The mean vector of the corrected known parameters is as follows:

[0138]

[0139] Example

[0140] There is a real power plant with a low-pressure cylinder and its corresponding regenerative heater, which together form a thermodynamic system. The types and locations of the measuring points in this system are as follows: Figure 2As shown. There are three types of measuring points in a power plant: temperature (T), pressure (P), and flow (M). It is important to note that the units of measurement for the same type of measuring point may differ; therefore, all measurement data must be converted to the same unit system before calculation. When selecting measuring data, data from relatively stable operating conditions should be chosen whenever possible, and large fluctuations in the measured values ​​should be avoided.

[0141] In this embodiment of the invention, the specific steps for correcting the actual data of each component in the relevant thermal system are as follows:

[0142] 1) Based on the actual power plant system and instrument layout, for the low-pressure cylinder-regenerative heater system, the actual system's measuring point layout is analyzed and ordered sequentially: EXS-P, EX-P, SD-P, FWI-M, FWI-P, FWI-T, FWO-T, FWD-T. For example... Figure 2 As shown, by combining the component characteristic parameters and the known boundary parameters, the known parameter vector x can be obtained, which has the following form:

[0143] x = (x1, x2, ..., x 20 (27)

[0144] In addition to the eight measuring points mentioned above, the known parameter vector x also includes component characteristic parameters, namely, heat exchanger heat transfer coefficient, heat transfer area, heat exchanger design feedwater terminal difference, design condensate terminal difference, turbine isentropic efficiency, dehumidification efficiency, and pressure ratio, and known boundary parameters, namely, turbine upstream enthalpy, flow rate, heat exchanger upstream condensate flow rate, other heating steam enthalpy, and other heating steam flow rate. The correspondence of the above parameters is shown in the table below:

[0145]

[0146]

[0147] Based on the known data, the unknown physical property parameter vector y can be obtained. Based on the energy balance and mass balance relationships, combined with the component characteristics, the unknown parameter vector z of the current system can be established, which has the following form:

[0148] y = (y1, y2, ..., y9) (28)

[0149] z = (z1, z2, ..., z8) (29)

[0150] The components of the unknown physical property parameter vector y represent the ideal enthalpy of the isentropic enthalpy drop of the steam turbine, the enthalpy after the steam turbine stage, the enthalpy at the inlet of the heat exchanger feedwater, the enthalpy at the outlet, the enthalpy of the upper stage condensate, the enthalpy of the condensate in this stage, the saturated water enthalpy of the extraction steam temperature and pressure, and the exhaust dryness fraction. The correspondence between the above parameters is shown in the table below:

[0151] Physical properties significance Physical properties significance <![CDATA[y1]]> Ideal enthalpy value of isentropic enthalpy drop in steam turbine <![CDATA[y6]]> Enthalpy of condensate in heat exchanger stage <![CDATA[y2]]> Steam turbine stage after enthalpy <![CDATA[y7]]> extraction temperature <![CDATA[y3]]> enthalpy of heat exchanger feedwater inlet <![CDATA[y8]]> saturated water enthalpy of extraction steam pressure <![CDATA[y4]]> enthalpy of heat exchanger feedwater outlet <![CDATA[y9]]> Exhaust dryness <![CDATA[y5]]> Enthalpy of upper stage condensate of heat exchanger

[0152] The unknown parameter vector z represents the heat exchanger power, actual feedwater temperature difference, actual condensate temperature difference, extraction steam flow rate, extraction steam enthalpy, enthalpy after dehumidification, flow rate after dehumidification, and actual pressure ratio, respectively. The correspondence between the above parameters is shown in the table below:

[0153]

[0154]

[0155] The above components have the following equilibrium relationship based on mass and energy balance:

[0156]

[0157] In addition to the known parameters used in the basic solution above, the remaining parts can be used to establish a redundancy balance equation, resulting in the system's residual vector R = (R1, R2, R3, R4). The calculation methods for each component are as follows:

[0158]

[0159] 2) For steam turbines and their associated extraction steam pipelines that employ dehumidification technology, establish dehumidification model equations.

[0160] For a steam turbine employing dehumidification technology and its associated extraction steam pipes, the following relationship can be obtained from the dehumidification model:

[0161] z6-x 16 =x 14 (z6-y8)(1-y9)(32)

[0162] For the dehumidification unit and corresponding regenerative heater in the steam turbine, the following equilibrium relationship related to the dehumidification model can be obtained by utilizing mass and energy balance:

[0163]

[0164] 3) Generate the mean and covariance matrix based on the measurement data and instrument uncertainty information of the power plant over a certain period of time. By selecting the measurement values ​​of the measuring points in the power plant over a period of time, the mean of the measurement values ​​of each measuring point is calculated by equation (10). And obtain the variance estimate based on the instrument uncertainty. For the variance estimate, the uncertainty relationship between each known parameter can be further calculated using equation (11), and the covariance matrix X between each known parameter can be constructed. cThe correlation coefficients involved were determined based on historical operating data of real power plants and combined with engineering experience. The covariance matrix mentioned above reflects the statistical characteristics of the current system operation and can characterize the statistical distribution of the measured values ​​at the measuring points, serving as the main basis for subsequent correction of the measured values.

[0165] 4) Solve the heat balance model and dehumidification model to obtain data on unknown variables of the system.

[0166]

[0167] For the above multivariate nonlinear equation system, the Newton-Raphson iterative method is used to solve it. Let the above multivariate nonlinear equation system be F(z) = 0. After calculating the Jacobian matrix J(z) of the equation system by equation (13), construct the iterative format as shown in equation (14), and stop the calculation after iteratively solving until the accuracy is satisfied, so as to obtain the numerical solution of all unknown parameters in the equation system.

[0168] 5) Calculate the Jacobian matrix of the current system residuals with respect to the known parameter variables using the redundant balance equations. To measure the overall error level of the system under its current operating conditions, the residuals can be calculated using the redundant part of the balance equations mentioned above. From this, the Jacobian matrix J of the redundant balance equations with respect to the known parameter x can be obtained. R,x To calculate the Jacobian matrix mentioned above, it is necessary to calculate the Jacobian matrix J of the unknown parameter z of the power plant with respect to the known parameter x. z,x And the Jacobian matrix J of the redundant balance equation with respect to the unknown parameter z of the power plant R,z From equation (16), the Jacobian matrix J of the system residuals with respect to the known parameters is calculated according to the chain rule. R,x

[0169] 6) Calculate the correction amount for the known parameter variables. Based on the Jacobian matrix J calculated above... R,x The residuals of the system redundancy balance equations are calculated using the mean of the measured values ​​at the measurement points and the elements of the covariance matrix. Based on the above conditions, the corrections for all known parameters within the system can be calculated. The mean values ​​of the unknown parameters and the mean of the system balance equation residuals can be calculated based on the mean of the known system parameters. According to equation (19), the covariance matrix X of the residual vector of the system equilibrium equation can be calculated. R Given the parameter correction amount c, we have the following constrained optimization problem:

[0170]

[0171] To address the optimization problem described above, the Lagrange multiplier method is used. By introducing the Lagrange multiplier variable λ, the problem can be equivalently transformed into the following form:

[0172]

[0173] The expression for the correction quantity is obtained by solving based on the stationary point conditions as follows:

[0174]

[0175] After transforming the expression for the correction using the Jacobian matrix and calculating the Lagrange multiplier λ according to the constraints, substituting it back into equation (23) yields the correction as follows:

[0176]

[0177] 7) Calculate the corrected measurement point values ​​and steam extraction dehumidification parameters. The final correction value 'c' obtained through the above calculations can be used as the final correction vector and appended to the mean vector of the original known parameters. The above steps complete the correction of the known parameters. The mean vector of the corrected known parameters is as follows:

[0178]

[0179] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A calculation method for steam turbine extraction dehumidification based on data correction, characterized in that, Includes the following steps: 1) Construct a thermal balance model for the low-pressure cylinder-regenerative heater system; 2) For the heat balance model constructed in step 1), establish dehumidification model equations for the steam turbine and its associated extraction steam pipes that employ dehumidification technology; and for the dehumidification efficiency... The definition is as follows: (5) In the formula, This indicates the enthalpy value of the working fluid at the inlet of the dehumidifier; This indicates the enthalpy value of the working fluid at the outlet of the dehumidifier; This indicates the saturated water enthalpy value corresponding to the current pressure of the working fluid in the dehumidifier; Indicates the dryness of the working fluid at the inlet of the dehumidifier; The following relationship applies to the mass and energy balance of dehumidifiers: (6) (7) In the formula, Indicates the working fluid flow rate at the inlet of the dehumidifier; This indicates the flow rate of the working fluid at the outlet of the dehumidifier; Indicates the working fluid flow rate at the dehumidification steam extraction pipeline; This indicates the enthalpy value of the working fluid at the dehumidification extraction steam pipeline. The heat exchange power of the shell side of the regenerator after dehumidification and steam extraction is: (8) In the formula, This indicates the heat exchange power of the regenerator; Indicates the flow rate of the upper drainage system; Indicates the hydrophobic enthalpy value of the upper level; Indicates the hydrophobic enthalpy value of this level; Indicates the flow rate of other heating steam; Indicates other heating vapor enthalpy values; By varying the parameters of the feedwater on the tube side of the regenerator heater, and based on energy balance, the following equilibrium relationship is obtained: (9) In the formula, This indicates the feedwater flow rate on the tube side of the regenerator heater; This indicates the enthalpy value of the feedwater outlet on the tube side of the regenerator heater; This represents the enthalpy value of the feedwater inlet on the tube side of the regenerator; thus, the calculation relationship from the inlet and outlet parameters of the separation and dehumidification device, and the parameters of the extraction steam pipeline to the corresponding measured values ​​at the measuring points of the regenerator is established; 3) Based on the measurement point information involved in the model established in step 2), use the measurement data and instrument uncertainty information of the power plant within a certain period of time to generate the mean and covariance matrix; 4) Based on the measurement data from step 3), solve the heat balance model and dehumidification model to obtain the data of unknown variables in the system; 5) Based on the calculation results of the unknown variables in step 4), calculate the Jacobian matrix of the current system residuals with respect to the known parameter variables using the redundancy balance equation; 6) Calculate the correction amount of the known parameters based on the Jacobian matrix obtained in step 5); 7) Based on the parameter correction amount calculated in step 6), calculate the corrected measurement point value and the steam extraction dehumidification parameter.

2. The calculation method for turbine extraction dehumidification based on data correction according to claim 1, characterized in that, In step 1), the following relationship is established using measurement information from the power station: (1) In the formula, The known parameters of the low-pressure cylinder or regenerative heater of the power plant include the vector of measured values ​​of relevant measuring points in actual layout and the known component characteristic parameters; the measuring points include three types: flow rate, temperature and pressure, and the component characteristic parameters include the heat transfer coefficient and heat transfer area of ​​the heat exchanger and the isentropic efficiency of the steam turbine; This represents unknown physical property parameters obtained through measurements and their relationship to the working fluid's physical properties. These represent unknown parameters in the power plant system. They are certain physical quantities calculated using known measurements and unknown physical properties, or the transfer of measurements and the increase or decrease in mass flow rate due to the confluence and diversion of working fluids in pipelines. The system thermal balance model is established based on the two principles of mass balance and energy balance. For the sequence number... A certain component has the following mass balance equation: (2) In the formula, Indicates components The residuals of the mass balance equation Indicates components The total flow rate of the input working fluid, Indicates components The total outflow of the working fluid is calculated using absolute values. For a given component, the following energy balance equation applies: (3) In the formula, Indicates a certain component The residuals of the energy balance equation Indicates a certain component The total energy input, Indicates a certain component The total energy flowing out; all energy values ​​are calculated using absolute values; combining the balance equations of each component, the residual vector of the overall system balance equation is obtained as follows: (4) In the formula, Represents the residual vector of the current equilibrium equation of the system; This refers to some known parameters in the system, specifically the remaining known parameters in the system other than those used for solving unknown parameters.

3. The method for calculating turbine extraction dehumidification based on data correction according to claim 2, characterized in that, In step 3), the operating parameters of a certain component of the system over a period of time are... Selected The measurement results yielded a series of values: Then the mean value of the measured values ​​at this measuring point is: (10) In the formula, This is the estimated mean value at this measuring point; in addition to the mean of the measured values, instrument uncertainty is also needed to measure the randomness of the fluctuations in the measured values ​​at the measuring point over a period of time, thus obtaining the covariance matrix between the measured values ​​at the measuring point. Its elements are calculated as follows: (11) In the formula, These are the elements in the covariance matrix; The variance of the measured values ​​at the measuring points; The correlation coefficient between the measuring points is determined based on historical operating data of the actual power plant and combined with engineering experience.

4. The calculation method for turbine extraction dehumidification based on data correction according to claim 3, characterized in that, In step 4), for the dehumidification device and corresponding regenerative heater in the steam turbine, the following set of equations is obtained based on the mass and energy balance and the dehumidification model: (12) This system of equations is a multivariate nonlinear system, solved using the Newton-Raphson iterative method; the above-mentioned nonlinear system of equations is... Then the Jacobian matrix of this system of equations is defined as: (13) After obtaining its Jacobian matrix, the following iterative scheme is constructed: (14) In the formula, For the number of iterations, Indicates the first Solution of the iterative system of equations ; express The inverse of the Jacobian matrix; initially from Start by setting the iterative solution precision. The iterative process should solve the following system of linear equations: (15) Solve from the above formula ,when When the condition is met, it indicates that the iteration has converged and the accuracy requirement is satisfied, and the iteration process terminates; otherwise, it is set to zero. Continue iteratively to solve the problem.

5. The method for calculating turbine extraction dehumidification based on data correction according to claim 4, characterized in that, In step 5), to measure the overall error level of the system under its current operating conditions, the redundant part of the balance equation is used to calculate the system residuals, thereby obtaining the redundant balance equation with respect to the known parameters. Jacobian matrix To calculate the Jacobian matrix, the unknown parameters of the power station need to be calculated separately. Regarding known parameters Jacobian matrix And the redundant balance equations regarding the unknown parameters of the power plant Jacobian matrix Calculate the Jacobian matrix using the chain rule. for: (16)。 6. The method for calculating turbine extraction dehumidification based on data correction according to claim 5, characterized in that, In step 6), based on the calculated Jacobian matrix... The residuals of the system's redundant balance equations are calculated using the known parameter variables' means and elements of the covariance matrix. Based on the above conditions, the correction amounts for all known parameters within the system can be calculated. The mean values ​​of the unknown parameters and the system's balance equation residuals are then calculated based on the mean values ​​of the known system parameters. (17) (18) In the formula, , and These are the mean vectors of the unknown physical property parameters, known parameters, and unknown parameters in the system, respectively. and These are the mean vectors of the residuals and some known parameters in the system, respectively; from this, the covariance matrix of the residual vector of the system equilibrium equation can be calculated. : (19) For known parameter correction amount The following is a constrained optimization problem: (20) The objective of this constrained optimization problem is to find a solution that satisfies the optimization function. The goal is to find the minimum value, i.e., the minimum correction amount, so that the residual of the system equilibrium equation is zero. The Lagrange multiplier method is applied to the above optimization problem, introducing Lagrange multiplier variables. Then the problem is equivalently transformed into the following form: (21) The expression for the correction quantity obtained by solving based on the stationary point conditions is as follows: (22) For the above formula The result is still unknown, so both sides of the equation are multiplied on the left by the Jacobian matrix. The above expression can be transformed into the following form: (23) Based on the constraints of this optimization problem Solving for the Lagrange multipliers, we get: (24) Substituting the above equation back into equation (23), we obtain the final solution for the correction: (25) Through the above process, the correction amount of each known parameter can be solved; While ensuring the optimization objective function is minimized, the residuals of the system redundancy balance equations are reduced to the minimum.

7. The calculation method for turbine extraction dehumidification based on data correction according to claim 6, characterized in that, In step 7), the final solution obtained through calculation is the correction amount. This is then appended as the final correction vector to the mean vector of the original known parameters. The above steps complete the correction of the known parameters. The mean vector of the corrected known parameters is as follows: (26)。

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